A social matching system for an online dating network
A number of social network services have developed solutions to accommodate users participating in social networks through use of wireless devices, and other portable electronic devices.Conventional social networking solutions, such as online social networks, typically require a user who wants to find other members that share similar interests to designate the specific attributes sought at the same time as the user wants to find these members.This patent claims priority from the following provisional patent application: Application No. 20, 2008 and entitled “System and Method for Matching Social Network Users” which is incorporated herein by reference.A portion of the disclosure of this patent document contains material which is subject to copyright protection.Users of many conventional social networks may also search for individuals that one may have interest in by scanning though the profiles and data of users associated with already-known members.
For example, a user may enter data about the user stating that the user is funny and good-looking.
The system, in this example, would capture a high score for the “funny” attribute category and a high score for a “physical attractiveness” attribute category.
As an extension of the present example, the user may enter attributes regarding the prospects that the user would want to meet.
The process for a user to find prospects of interest may initiate with a user registering with an online system.
For example, the user may be asked to enter basic identifying information into the system, and may be prompted to enter further information (e.g., profile information) about the user as the user would like. A user may attach files such as one or more digital photograph files to a their profile.
As the attributes scores indicate the attributes that a user possesses, and the matching scores indicate the attributes that a user is seeking, by calculating the variance between the user's matching and the prospect's attribute scores, and the prospect's matching scores and the user's attribute scores, a nearest-to match can be derived.